Pricing

$5.00/month + usage

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Instagram Comments Scraper

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Developed by

Pratik Dani

The Instagram Comments Scraper is a tool designed to extract detailed comments from valid Instagram posts and reels. This actor provides a structured way to gather insights from user interactions on Instagram, making it easier to analyze engagement and sentiment.

5.0 (1)

Pricing

$5.00/month + usage

Total users

105

Monthly users

Runs succeeded

74%

Issues response

26 days

Last modified

4 months ago

Social media

Developer tools

Automation

You can access the Instagram Comments Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=pratikdani/instagram-comments-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Instagram Comments Scraper

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=pratikdani/instagram-comments-scraper along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=pratikdani/instagram-comments-scraper",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

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